As the population becomes increasingly dependent on computing resources, the need for more computers and access to them becomes larger and more important. Today, millions of people use computing devices with an ever increasing need to have access to them. As a consequence, computing administrators need to be able to accommodate this need and be able to adapt to the volume of software instructions given to computing devices by the many users as well as the numerous applications that run on them. However, a problem remains as to how to adequately determine when a computer has reached its maximum or some desired capacity. For example, a typical computer may need to handle millions of instructions from a few applications but also may need to handle a group of new users. A challenge is be able to forecast when a computer or set of computers has reached its capacity in executing both instruction sets from the various applications running on it as well as its ability to handle an increasing number of users wanting access to computing resources.
In the past, thorough testing was required to stress test a system to determine a computer's expected capacity which is a trial-by-error approach. The process entailed estimating the expected transaction volumes that may push a computer beyond its ability to complete transactions in question. Because of the variety of transactions and types of computers, the testing method would get expensive and be time consuming in determining the right mix of transactions to use and estimating the correct load inputs to be placed on the types of computers. The maximum capacity would be observed if the transaction volume pushed the computer beyond its threshold. Setting up and maintaining a testing environment is an expensive, resource-intensive process. Moreover, testing environments are not the same as real-world production environments.
In today's world, numerous computers are dispersed throughout many networks covering a range of applications and activities. The expectation is that these computers are always working to provide the response time as defined in contracted service level agreements. Unfortunately, users and application executions are increasing at an alarming rate placing enormous burdens on system resources. A challenge has become a battle to keep pace with these demands by checking and maintaining computers very often to insure that they can handle the capacity needs placed upon them by the ever increasing number of users and demand for executing more applications.